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A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis

The objective of this research was set to propose a supervised ANN method able to perform data classification and data structure, inter-neuron distances and data topology preserved visualization simultaneously. A real world application of mental disorder diagnosis in counseling domain was then inves...

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Bibliographic Details
Main Author: Md. Sarwar, Zahan Tapan
Format: Thesis
Language:English
Published: 2008
Subjects:
QA76 Computer software
Online Access:http://ir.unimas.my/id/eprint/402/8/Md.%20Sarwar%20Zahan%20Tapan%20%28full%29.pdf
http://ir.unimas.my/id/eprint/402/
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id my.unimas.ir.402
record_format eprints
spelling my.unimas.ir.4022023-03-30T04:03:20Z http://ir.unimas.my/id/eprint/402/ A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis Md. Sarwar, Zahan Tapan QA76 Computer software The objective of this research was set to propose a supervised ANN method able to perform data classification and data structure, inter-neuron distances and data topology preserved visualization simultaneously. A real world application of mental disorder diagnosis in counseling domain was then investigated and LVQ with AC was employed to facilitate classification and visualization in designing and development of an intelligent decision support system to assist counselors in diagnosis of mental disorders. 2008 Thesis NonPeerReviewed text en http://ir.unimas.my/id/eprint/402/8/Md.%20Sarwar%20Zahan%20Tapan%20%28full%29.pdf Md. Sarwar, Zahan Tapan (2008) A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis. Masters thesis, Universiti Malaysia Sarawak (UNIMAS).
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Md. Sarwar, Zahan Tapan
A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis
description The objective of this research was set to propose a supervised ANN method able to perform data classification and data structure, inter-neuron distances and data topology preserved visualization simultaneously. A real world application of mental disorder diagnosis in counseling domain was then investigated and LVQ with AC was employed to facilitate classification and visualization in designing and development of an intelligent decision support system to assist counselors in diagnosis of mental disorders.
format Thesis
author Md. Sarwar, Zahan Tapan
author_facet Md. Sarwar, Zahan Tapan
author_sort Md. Sarwar, Zahan Tapan
title A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis
title_short A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis
title_full A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis
title_fullStr A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis
title_full_unstemmed A novel hybrid supervised artificial neural network (ANN) for data visualization and classification to the application of mental disorder diagnosis
title_sort novel hybrid supervised artificial neural network (ann) for data visualization and classification to the application of mental disorder diagnosis
publishDate 2008
url http://ir.unimas.my/id/eprint/402/8/Md.%20Sarwar%20Zahan%20Tapan%20%28full%29.pdf
http://ir.unimas.my/id/eprint/402/
_version_ 1762396649829695488
score 13.149126

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